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Record W3199729393 · doi:10.46692/9781447305736.008

Abuse, Mistreatment and Neglect

2020· other· en· W3199729393 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsNeglectPsychologyMedical emergencyPsychiatryMedicineClinical psychology

Abstract

fetched live from OpenAlex

The focus of Chapter 6 is the abuse, mistreatment and neglect of older people. It is a cross-cutting issue that spans settings and contexts and is self-evidently damaging to well-being and to physical and mental health (Milne et al, 2013). Prevalence and incidence of abuse will be discussed first before reviewing what is known about its causes, nature and impact. It is important to note that mental ill health intersects with abuse and mistreatment in at least two overarching ways: older people with mental illness, especially dementia, are at heightened risk of abuse; and older people who are victims of abuse are at risk of poorer mental health. Prevalence and incidence of abuse and neglect of older people Due to the fact that abuse of older people occurs ‘behind closed doors’ and often goes unreported, accurate statistics about its prevalence and incidence are difficult to obtain. Current estimates suggest that between 2 per cent and 10 per cent of older people suffer ‘some form of abuse’. Randomised, community-based epidemiological studies have reported annual rates of between 2 per cent and 4 per cent in the United States, Canada and Europe (Sethi et al, 2011). The 2007 UK Study of Abuse and Neglect of Older People identified that 8.6 per cent of older people (those aged 66 years or over) living in the community experienced some form of ‘mistreatment’ (O’Keefe et al, 2007). ‘Mistreatment’ was defined as physical, psychological, sexual or financial abuse or neglect. The survey identified that the prevalence of mistreatment increased with declining health of the victim; it also noted the particular vulnerability of very elderly people who have complex comorbid health conditions (O’Keefe et al, 2007). Action on Elder Abuse (a charity) estimates that at least 500,000 older people are abused each year in the UK (2004). Data drawn from ‘adult safeguarding systems’ suggest that older women make up the vast majority of victims (Milne et al, 2013). Studies focusing on older people dependent on family carers report that approximately a quarter have experienced significant psychological abuse and a fifth neglect (Hirsch and Vollhardt, 2008; Association of Directors of Adult Social Services, 2011). In studies with well-defined target populations, 11 to 20 per cent of family carers reported physically abusing the relative they support and 37 to 55 per cent reported verbally abusing or neglecting them (Cooper et al, 2008).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0190.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.276
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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